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We present a value profile based approach for ranking program statements according to their likelihood of being faulty. The key idea is to see which program statements exercised during a failing run use values that can be altered so that the execution instead produces correct output. Our approach is effective in locating statements that are either faulty or directly linked to a faulty statement. We present experimental results showing the effectiveness and efficiency of our approach. Our approach outperforms Tarantula which, to our knowledge, is the most effective prior approach for statement ranking based fault localization using the benchmark programs we studied.
Jeffrey et al. (Sun,) studied this question.
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